# How to integrate Google Meet MCP with LlamaIndex

```json
{
  "title": "How to integrate Google Meet MCP with LlamaIndex",
  "toolkit": "Google Meet",
  "toolkit_slug": "googlemeet",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/googlemeet/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/googlemeet/framework/llama-index.md",
  "updated_at": "2026-05-12T10:13:58.785Z"
}
```

## Introduction

This guide walks you through connecting Google Meet to LlamaIndex using the Composio tool router. By the end, you'll have a working Google Meet agent that can schedule a new video meeting for tomorrow, list all meetings i hosted last week, get transcript from your most recent meeting through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Google Meet account through Composio's Google Meet MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Google Meet with

- [ChatGPT](https://composio.dev/toolkits/googlemeet/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/googlemeet/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/googlemeet/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/googlemeet/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/googlemeet/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/googlemeet/framework/codex)
- [Cursor](https://composio.dev/toolkits/googlemeet/framework/cursor)
- [VS Code](https://composio.dev/toolkits/googlemeet/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/googlemeet/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/googlemeet/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/googlemeet/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/googlemeet/framework/cli)
- [Google ADK](https://composio.dev/toolkits/googlemeet/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/googlemeet/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/googlemeet/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/googlemeet/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/googlemeet/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Google Meet
- Connect LlamaIndex to the Google Meet MCP server
- Build a Google Meet-powered agent using LlamaIndex
- Interact with Google Meet through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## What is the Google Meet MCP server, and what's possible with it?

The Google Meet MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Meet account. It provides structured and secure access to your meetings and recordings, so your agent can schedule new meetings, fetch past conference details, access recordings and transcripts, and manage meeting spaces on your behalf.
- Instant meeting scheduling and management: Ask your agent to create new Google Meet sessions or update existing meeting spaces with specific settings and access controls.
- Comprehensive meeting record retrieval: Have your agent list all past conference records, filter them by time or criteria, and pull up detailed information about any meeting.
- Access recordings and transcripts: Effortlessly retrieve recordings or full transcripts of your previous Google Meet conferences for reference, review, or sharing.
- Participant session insights: Let your agent list all participants in a given meeting or fetch detailed information about specific attendee sessions for attendance tracking or follow-up.
- Flexible post-meeting actions: Enable your agent to update meeting spaces, manage access, and ensure your Google Meet environment stays organized and up to date.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GOOGLEMEET_CREATE_MEET` | Create Google Meet Space | Creates a new Google Meet space with optional configuration. Does not attach to any calendar event — calendar linking requires a separate Calendar tool call. Capture `meetingUri`, `meetingCode`, and `space.name` from the response immediately for downstream lookups. Requires `meetings.space.created` OAuth scope. Returns HTTP 429 under rapid calls; apply exponential backoff. Use when you need a meeting space with specific access controls, moderation, recording, or transcription settings. |
| `GOOGLEMEET_END_ACTIVE_CONFERENCE` | End active conference | Ends an active conference in a Google Meet space. REQUIRES 'space_name' parameter (e.g., 'spaces/jQCFfuBOdN5z' or just 'jQCFfuBOdN5z'). Use when you need to terminate an ongoing conference in a specified space. This operation only succeeds if a conference is actively running in the space. You must always provide the space_name to identify which space's conference to end. Immediately drops all active participants — obtain explicit user confirmation before calling. |
| `GOOGLEMEET_GET_CONFERENCE_RECORD_BY_NAME` | Get conference record by name | Tool to get a specific conference record by its resource name. Use when you have the conference record ID and need to retrieve detailed information about a single meeting instance. |
| `GOOGLEMEET_GET_MEET` | Get Meet details | Retrieve details of a Google Meet space using its unique identifier. Newly created spaces may return incomplete data; retry after 1–3 seconds if needed. |
| `GOOGLEMEET_GET_PARTICIPANT_SESSION` | Get Participant Details | Retrieves detailed information about a specific participant session from a Google Meet conference record. Returns session details including start time and end time for a single join/leave session. A participant session represents each unique join or leave session when a user joins a conference from a device. If a user joins multiple times from the same device, each join creates a new session. PREREQUISITE: You must first obtain the participant session resource name. Use LIST_PARTICIPANT_SESSIONS with a conference record ID and participant ID to get available sessions and their resource names. The 'name' parameter is REQUIRED and must be in the format: 'conferenceRecords/{conference_record}/participants/{participant}/participantSessions/{participant_session}' |
| `GOOGLEMEET_GET_RECORDINGS_BY_CONFERENCE_RECORD_ID` | Get recordings by conference record ID | Retrieves recordings from Google Meet for a given conference record ID. Only returns recordings if recording was enabled and permitted by the organizer's domain policies; a valid conference_record_id does not guarantee recordings exist. After a meeting ends, recordings may take several minutes to process — an empty result may be temporary, not permanent. |
| `GOOGLEMEET_GET_TRANSCRIPT` | Get Transcript | Retrieves a specific transcript by its resource name. Returns transcript details including state (STARTED, ENDED, FILE_GENERATED), start/end times, and Google Docs destination. PREREQUISITE: Obtain the transcript resource name first by using GET_TRANSCRIPTS_BY_CONFERENCE_RECORD_ID or construct it from known IDs. |
| `GOOGLEMEET_GET_TRANSCRIPT_ENTRY` | Get Transcript Entry | Fetches a single transcript entry by resource name for targeted inspection or incremental processing. Use when you have a specific transcript entry resource name and need to retrieve its details (text, speaker, timestamps, language). PREREQUISITE: Obtain the transcript entry resource name first by using LIST_TRANSCRIPT_ENTRIES or construct it from known IDs. The 'name' parameter is REQUIRED and must follow the format: 'conferenceRecords/{conferenceRecordId}/transcripts/{transcriptId}/entries/{entryId}' |
| `GOOGLEMEET_GET_TRANSCRIPTS_BY_CONFERENCE_RECORD_ID` | Get transcripts by conference record ID | Retrieves all transcripts for a specific Google Meet conference using its conference_record_id. Transcripts require processing time after a meeting ends — empty results may be transient; retry after a delay before concluding no transcripts exist. Returns results only if transcription was enabled during the meeting and permitted by the organizer's domain policies; an empty list may also indicate transcription was never generated. |
| `GOOGLEMEET_LIST_CONFERENCE_RECORDS` | List Conference Records | Tool to list conference records. Use when you need to retrieve a list of past conferences, optionally filtering them by criteria like meeting code, space name, or time range. |
| `GOOGLEMEET_LIST_PARTICIPANTS` | List Participants | Lists the participants in a conference record. By default, ordered by join time descending. Use to retrieve all participants who joined a specific Google Meet conference, with support for filtering active participants (where `latest_end_time IS NULL`). |
| `GOOGLEMEET_LIST_PARTICIPANT_SESSIONS` | List Participant Sessions | Lists all participant sessions for a specific participant in a Google Meet conference. A participant session represents each unique join or leave session when a user joins a conference from a device. If a user joins multiple times from the same device, each join creates a new session. Returns session details including start time and end time for each session. |
| `GOOGLEMEET_LIST_RECORDINGS` | List Recordings | Tool to list recording resources from a conference record. Use when you need to retrieve recordings from a specific Google Meet conference. Recordings are created when meeting recording is enabled and saved to Google Drive as MP4 files. |
| `GOOGLEMEET_LIST_TRANSCRIPT_ENTRIES` | List Transcript Entries | Tool to list structured transcript entries (speaker/time/text segments) for a specific Google Meet transcript. Use when you need to access the detailed content of a transcript, including individual spoken segments with timestamps and speaker information. Note: The transcript entries returned by the API might not match the transcription in Google Docs due to interleaved speakers or post-generation modifications. |
| `GOOGLEMEET_UPDATE_SPACE` | Update Google Meet Space | Updates the settings of an existing Google Meet space. Requires organizer/host privileges and the meetings.space.created OAuth scope. REQUIRED PARAMETER: - name: The space identifier (e.g., 'spaces/jQCFfuBOdN5z'). This is always required to identify which space to update. OPTIONAL PARAMETERS: - config: The new configuration settings to apply (accessType, entryPointAccess, moderation, etc.) - updateMask: Specify which fields to update. If omitted, all provided config fields are updated. Example: To change access type, provide name='spaces/abc123' and config={'accessType': 'OPEN'} |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Google Meet MCP server is an implementation of the Model Context Protocol that connects your AI agent to Google Meet. It provides structured and secure access so your agent can perform Google Meet operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Google Meet account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Google Meet

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Google Meet access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, google meet)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Google Meet tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["googlemeet"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Google Meet actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Google Meet actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["googlemeet"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Google Meet actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Google Meet
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Google Meet, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["googlemeet"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Google Meet actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Google Meet actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["googlemeet"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Google Meet actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Google Meet to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Google Meet tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Google Meet MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/googlemeet/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/googlemeet/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/googlemeet/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/googlemeet/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/googlemeet/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/googlemeet/framework/codex)
- [Cursor](https://composio.dev/toolkits/googlemeet/framework/cursor)
- [VS Code](https://composio.dev/toolkits/googlemeet/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/googlemeet/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/googlemeet/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/googlemeet/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/googlemeet/framework/cli)
- [Google ADK](https://composio.dev/toolkits/googlemeet/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/googlemeet/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/googlemeet/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/googlemeet/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/googlemeet/framework/crew-ai)

## Related Toolkits

- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.
- [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Chatwork](https://composio.dev/toolkits/chatwork) - Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity.
- [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease.
- [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.
- [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms.
- [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.
- [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices.
- [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels.
- [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks.
- [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission.
- [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security.
- [Heartbeat](https://composio.dev/toolkits/heartbeat) - Heartbeat is a plug-and-play platform for building and managing online communities. It helps you organize users, channels, events, and discussions in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Google Meet MCP?

With a standalone Google Meet MCP server, the agents and LLMs can only access a fixed set of Google Meet tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Google Meet and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Google Meet tools.

### Can I manage the permissions and scopes for Google Meet while using Tool Router?

Yes, absolutely. You can configure which Google Meet scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Google Meet data and credentials are handled as safely as possible.

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